Cognitive science based inclusive border management system

Abstract

Cross border infiltration or surpassing is an illegal attempt of crossing the international border to carry out abnormal activities. Many threats such as terrorist is one of the major issue in international community. Every country wants their nation to be free from all types of threats and can maintain the harmony of the nation. To protect from these type of cross border activity, Inclusive Border Management System (IBMS) is proposed which is expected to decrease the penetration at borders of nations. It is a coordination of labor, sensor, computer networks, insight and control arrangements. It incorporates Electro Optic Sensors (high determination day and night camera) radars and the preferences. This work is expected to make a reference library on threat signature utilizing intellectual innovation which will upgrade the knowledge for IBMS. The goal of this work is to reduce the miss rate radically by perusing the administrators brainwave examples and utilizing them to decide whether it has been identified a conceivable threat without monitoring it. This cap system proposes to utilize an Electroencephalogram (EEG) cap to capture the observer brain signals and afterward records when the observer identifies a threat. The combination of algorithm and EEG brain waves not just reduces false alerts, it additionally causes spectators to distinguish indications of threats that would be disregarded, for example, flying feathered creatures, influencing branches or non threat protest agreeing the activity recognition. This examination means to recommend a superior streamlining method on P300 signals and build an operational library of threat signature.